The Role of Biomarkers in Early Detection of Chronic Disease Risk and Smoking Cessation Efforts among Students, Indonesia

This cross-sectional study of 563 Indonesian high school students reveals that high cotinine levels, indicating significant nicotine exposure and chronic disease risk, are primarily driven by daily cigarette consumption, male gender, having smoking family members, and low physical activity, though these factors did not significantly correlate with a willingness to join smoking cessation programs.

The Gist

Imagine a group of high school students in a district in Indonesia. Some of them smoke, some are just hanging out with smokers, and some are trying to quit. The researchers wanted to know: Who is actually getting hit by the smoke, and what does that mean for their future health?

To find out, they didn't just ask the kids, "Do you smoke?" (because people sometimes lie or forget). Instead, they used a biological "smoke detector" called a biomarker.

Here is the story of the study, broken down into simple terms:

1. The "Smoke Detector" (Cotinine)

Think of cotinine as a "receipt" your body keeps after you've been around cigarette smoke. When you smoke (or breathe in someone else's smoke), your body turns the nicotine into cotinine. It stays in your system for a day or two, like a stain on a shirt that won't wash out immediately.

The researchers tested the students' urine to see how much "stain" (cotinine) was there.

• Low Level: The shirt is mostly clean.
• High Level: The shirt is soaked. This means the student is either smoking heavily or breathing in a lot of secondhand smoke.

The Shocking Result: They found that 67% of the students had "soaked shirts." Even though not everyone admitted to smoking, the test showed that two out of every three students were getting a heavy dose of nicotine.

2. Who Has the "Soaked Shirts"? (The Risk Factors)

The researchers looked for clues to see who was most likely to have high levels. They found five main "leaks" in the system:

• The Gender Gap: Boys were much more likely to have high levels than girls. It's like a club where the rules are more relaxed for the guys, making it easier to get into the habit.
• The Family Smoke Cloud: If your parents or siblings smoke at home, you are almost twice as likely to have high levels. Imagine living in a house where the air is always hazy; even if you don't light a cigarette, you're breathing it in.
• The "Heavy Hitter" Habit: Students who smoked 5 or more cigarettes a day had the highest levels. The more you smoke, the bigger the "stain."
• The Couch Potato Effect: Students who rarely exercised were more likely to have high levels. It's like a car that sits in the garage too long; it doesn't get cleaned out. Active bodies seem to handle smoke better, or perhaps people who exercise just make different lifestyle choices.
• The Warning Signs: Students who already had a chronic cough, trouble breathing, or a history of illness were more likely to have high levels. Their bodies were already sounding the alarm bells, but the smoke was still pouring in.

3. The Willingness to Quit (The Paradox)

Here is the interesting part: Even though most students had high levels of smoke in their bodies, more than half said they wanted to quit.

However, the study found a tricky gap:

• Just saying "I want to quit" or "I'm willing to join a program" didn't automatically mean their smoke levels were lower.
• It's like saying, "I want to lose weight," but still eating the cake. The desire is there, but the action hasn't caught up yet.
• Interestingly, students who were unsure about quitting ("I might, I might not") actually had higher smoke levels than those who said "No way, I'm never quitting." This suggests that the people who are confused and hesitant are the ones most stuck in the habit.

4. The Big Picture: Why This Matters

Think of the body like a house. Smoking is like letting smoke fill the rooms.

• Short term: The house gets smelly (coughing, shortness of breath).
• Long term: The smoke damages the walls and the foundation (heart disease, lung cancer, diabetes).

This study shows that many teenagers are already living in a "smoky house" without even realizing how bad it is. Because they are young, they think they are invincible. But the "receipt" (cotinine) proves they are already paying the price.

The Takeaway

The researchers suggest that schools shouldn't just lecture students about smoking. Instead, they should use the "Smoke Detector" test as a wake-up call.

Imagine showing a student their own urine test result: "Look, your body is full of smoke right now." That concrete proof might be the push they need to finally open the windows, stop smoking, and clean up their house before the damage becomes permanent.

In short: Smoking (or breathing smoke) is already happening to most students. It's linked to their family habits, their gender, and how active they are. While many want to quit, they need real help and concrete evidence to actually do it before their future health goes up in smoke.

Technical Summary

Title

The Role of Biomarkers in Early Detection of Chronic Disease Risk and Smoking Cessation Efforts among Students, Indonesia

1. Problem Statement

Smoking is a primary risk factor for chronic diseases (e.g., COPD, cardiovascular disease, lung cancer), with a rising prevalence among adolescents in Indonesia. In West Nusa Tenggara (WNT), the smoking rate among teenagers reached 32.40% in 2024. Current prevention efforts face challenges due to a lack of awareness regarding long-term health effects and insufficient effective intervention programs in schools. There is a critical need for objective methods to detect nicotine exposure (both active and passive) to facilitate early risk detection and motivate smoking cessation before chronic conditions develop.

2. Methodology

• Study Design: Cross-sectional study conducted from March to October 2025.
• Setting: Senior high schools in Praya Barat District, Central Lombok Regency, Indonesia.
• Participants: A total of 563 high school students (aged 15–18) were selected using a sample size calculation (OpenEpi).
  • Inclusion: Smokers, those exposed to secondhand smoke, and willing participants with parental consent.
  • Exclusion: Pre-existing diagnosed chronic diseases (prior to the study) and incomplete data.
• Data Collection:
  • Biomarker Analysis: Urine samples were analyzed for cotinine (a stable metabolite of nicotine with a 16–20 hour half-life) using a urine analyzer.
    • High Cotinine: ≥10 ng/mL (indicating active/passive exposure).
    • Low Cotinine: <10 ng/mL.
  • Questionnaires: Structured surveys collected data on demographics, smoking habits (cigarettes/day), family smoking status, physical activity, respiratory history (chronic cough, shortness of breath), and readiness to quit.
  • Reliability: The questionnaire had a Cronbach's Alpha of 0.716.
• Statistical Analysis:
  • Descriptive statistics for demographics.
  • Chi-square tests for bivariate associations.
  • Multiple Logistic Regression to determine independent predictors of high cotinine levels (Adjusted Odds Ratio [AOR] with 95% Confidence Interval [CI]).
  • Significance level set at p < 0.05.

3. Key Contributions

• Objective Biomarker Integration: The study moves beyond self-reported smoking data by utilizing urine cotinine levels as an objective biological indicator to quantify nicotine exposure among adolescents.
• Holistic Risk Factor Analysis: It identifies a complex interplay between behavioral factors (smoking intensity, physical activity), environmental factors (family smoking), and physiological markers (respiratory symptoms) in predicting high nicotine exposure.
• Policy Foundation: Provides empirical evidence to support the integration of biomarker-based screening into school health programs for early chronic disease prevention in Indonesia.

4. Key Results

• Prevalence of Exposure: 67% of the 563 students had high cotinine levels (≥10 ng/mL), indicating significant nicotine exposure.
• Demographics: The majority of respondents were male (62.5%).
• Significant Determinants (Multivariate Analysis):
  The following factors were significantly associated with high cotinine levels:
  1. Cigarette Consumption: Smoking ≥5 cigarettes/day (AOR = 2.426; p < 0.001).
  2. Gender: Male students were 2.1 times more likely to have high levels than females (AOR = 2.100; p = 0.001).
  3. Family Environment: Having family members who smoke (AOR = 2.149; p = 0.001).
  4. Physical Activity: Rarely exercising (AOR = 2.155; p = 0.001).
  5. Health History:
     • Personal history of chronic disease (AOR = 2.646; p < 0.001).
     • History of chronic cough (AOR = 2.103; p = 0.003).
     • History of shortness of breath (AOR = 2.000; p = 0.004).
     • Family history of chronic disease (AOR = 2.068; p = 0.003).
• Motivation to Quit:
  • While 53.6% expressed interest in quitting, the statistical analysis showed that willingness to participate in a smoking cessation program was NOT significantly associated with cotinine levels (p = 0.093).
  • However, being "unsure" about quitting was significantly associated with higher cotinine levels (AOR = 1.452; p = 0.017).

5. Significance and Conclusion

• Public Health Impact: The high prevalence of elevated cotinine levels (67%) among students signals a critical public health issue, indicating that a majority of adolescents are at risk for future chronic diseases due to active smoking or significant secondhand smoke exposure.
• Intervention Strategy: The study confirms that biomarker-based interventions are effective for objective detection. The findings suggest that interventions must be multi-faceted, targeting:
  • Gender-specific approaches (focusing on males).
  • Family-based education to reduce secondhand smoke exposure at home.
  • Lifestyle modifications promoting physical activity.
  • Motivational counseling for those who are ambivalent about quitting.
• Future Policy: The authors recommend integrating cotinine testing into school health policies to provide concrete biological feedback to students, thereby enhancing motivation for cessation and reducing the long-term burden of chronic non-communicable diseases in Indonesia.